FREE ONLINE WORKSHOP
Secure Data Sharing
with Differential Privacy & Federated Learning
May 22 | 9-11 AM | Teams
Join our Online Workshop on Industrial Data Privacy
Unlock the Power of Your Data – Securely
Join our hands-on workshop to discover practical tools for maximizing the value of your data — without compromising confidentiality. Learn how to analyze and share data securely, while unlocking new business opportunities.
We’ll dive into cutting-edge techniques like Federated Learning, which enables collaboration across organizational boundaries without exposing sensitive information — ideal for training AI models together without sharing raw data. You’ll also gain a clear understanding of privacy-enhancing technologies such as Differential Privacy, and how they can give your organization a real competitive edge.
Through real-world cases from Volvo CE and Sensative, you’ll see how industry leaders are already applying these methods to streamline operations and safeguard their data.
This workshop is more than just theory—it’s a chance to engage with experts, ask your burning questions, and connect with peers who are also navigating the future of data privacy and innovation.
Empower Your Data, Empower Your Future!
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• Welcome and introduction
– Johan Stenborg (Bron Innovation)• Why Secure Data Sharing is Important for Industrial Digitalization
– Henrik Abrahamsson (RISE)• Differential Privacy – An orientation
– David Eklund (RISE)• When to Use Federated Learning
– Sima Sinaei (RISE)• Business aspects on data sharing and privacy-preserving techniques – Fredrik Westman (Sensative)
• Privacy-preserving fall detection using federated machine learning – Axel Svegerud, Björn Dahlström (Lund University)
• Object Detection for Autonomous Machines through federated Learning
– Mohammad Loni (Volvo CE)• Interactive session with discussions
• Closing Remarks
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Maximize the Value of Your Data While Ensuring Privacy
Learn how to securely analyze and share data, unlocking new business opportunities.Enhance Collaboration Without Data Exposure
Discover how federated learning enables multiple stakeholders to train AI models together without sharing raw data.Gain Competitive Advantage
Implement privacy-preserving AI solutions that drive innovation in manufacturing, finance, healthcare, and smart cities.Learn from Real-World Cases
Hear directly from Volvo CE and Sensative on how they use these techniques to optimize operations and protect sensitive information.Engage with Experts & Peers
Get direct insights from leading researchers at RISE and industry leaders in privacy, AI, and industrial digitalization.
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Why Secure Data Sharing is Essential for Industrial Digitalization
Introduction to Differential Privacy & Its Industrial Applications
When & How to Use Federated Learning for AI Model Training
Real-World Case Studies: Volvo CE & Sensative
Interactive Discussion & Live Q&A